Outdoors
Local outdoor amenities, with a broader view of nearby nature.
- Data source
- OpenStreetMap
- Ranking layer
- Lifestyle Fit
- Base priority weight
- 15%
How CityFit computes this score
The local score combines OSM parks, reserves, trails, water access, viewpoints and peaks within 8 km of the stored city center. Where available, mapped park area is another component. CityFit then blends the local score with curated regional nature, water and terrain access scores. The final result never falls below the local score.
| Component | Relative weight | Full-score target |
|---|---|---|
| Parks and green space | 0.30 | 80 mapped places |
| Nature reserves and protected areas | 0.20 | 50 mapped places |
| Trails and mapped routes | 0.17 | 250 mapped places |
| Waterfront and water access | 0.20 | 1,000 mapped places |
| Viewpoints and peaks | 0.13 | 100 mapped places |
| Mapped park and green-space area | 0.12 | 8 km² |
From mapped places to a 0–100 score
- Collect mapped places. Query the relevant places around the stored city center through Overpass, an OpenStreetMap query service. Collections are cached instead of counted again on every visit.
- Adjust for land area. Use the land within the 8 km search circle, a reference area of about 201 km², and a maximum multiplier of four. If land-area data is missing, keep the original counts.
- Convert counts to scores. Logarithmic scoring gives additional places diminishing influence. Each component reaches 100 at its full-score target and is capped there.
- Combine the components. Take the weighted average of available scores and round to one decimal place. Divide relative weights by their total; they are not extra points.
View the scoring formula
adjusted_count = count × min(201.06 / max(land_area_km², 1), 4)
component_score = min(100 × ln(1 + adjusted_count) / ln(1 + target), 100)
score = sum(component_score × weight) / sum(available_weights)The 8 km circle is a consistent sampling area, rather than the city’s administrative boundary. Mapping completeness and tagging practices vary between cities. Missing collection values can be filled with zero by the score-building pipeline, so a low value can also reflect incomplete mapping.
The optional park-area component uses square kilometers directly in the logarithmic formula, with an 8 km² target. It does not receive the count-density adjustment. When present, its 0.12 weight joins the other component weights before normalization.
Adding regional nature access
The regional layer comes from CityFit’s curated regional access data. It combines 45% local outdoor score, 30% regional nature access, 15% water access and 10% terrain access. Available weights are normalized when data is missing.
View the scoring formula
regional_blend = weighted average(local, regional_nature, water, terrain)
final_outdoors_score = max(local_outdoor_score, regional_blend)Without regional data, CityFit keeps the local outdoor score.
How CityFit uses it
15% base weight in Lifestyle Fit. Your priority slider multiplies this weight, and CityFit takes the weighted average of the active lifestyle scores.
Changing priorities adjusts the blend; it does not recalculate the underlying outdoors score. The overall Practical Fit and Lifestyle Fit sliders determine how those two layers contribute to CityFit Score.
Country and region filters select which cities you see. Metric colors continue to use the global scale; percentiles describe a city’s standing across the full dataset and are separate from the raw score.
What the score can tell you
Regional scores are curated estimates. Neither the local counts nor the regional blend establish maintenance, trail difficulty, actual journey times, seasonal access or conditions.